Using multiple description (MD) coding mechanisms, this paper proposes a novel coding framework for error-resilience in distributed source coding (DSC) in sensor networks. In particular, scalable source descriptions are first generated using a symmetric scalable MD scalar quantizer. These descriptions are then layered Wyner-Ziv (WZ) coded using low-density parity-check accumulate (LDPCA) -based syndrome binning. The decoder consists of two side decoders which attempt to iteratively decode their respective description at various LDPCA puncturing rates in the presence of a correlated side information. A central decoder exploits the inter-description correlation to further enhance the WZ ratedistortion performance when both descriptions are partially or fully received. In contrast to earlier work, our proposed decoding scheme also exploits the correlation that exists between bit-planes. Experimental simulations reveal that, for a Gaussian source, the proposed system yields a performance improvement of roughly 0.66 dB when compared to not exploiting inter-description correlations.
Ceulemans, B, Satti, S, Deligiannis, N, Verbist, F & Munteanu, A 2014, Embedded Cross-Decoding Scheme for Multiple Description Based Distributed Source Coding. in 2014 Proceedings of the 22nd European Signal Processing Conference. Proceedings of the European Signal Processing Conference, IEEE, pp. 835-839, 22nd European Signal Processing Conference, EUSIPCO 2014, Lisbon, Portugal, 1/09/14.
Ceulemans, B., Satti, S., Deligiannis, N., Verbist, F., & Munteanu, A. (2014). Embedded Cross-Decoding Scheme for Multiple Description Based Distributed Source Coding. In 2014 Proceedings of the 22nd European Signal Processing Conference (pp. 835-839). (Proceedings of the European Signal Processing Conference). IEEE.
@inproceedings{33d828382eb1428fa3e3b3e41504acf2,
title = "Embedded Cross-Decoding Scheme for Multiple Description Based Distributed Source Coding",
abstract = "Using multiple description (MD) coding mechanisms, this paper proposes a novel coding framework for error-resilience in distributed source coding (DSC) in sensor networks. In particular, scalable source descriptions are first generated using a symmetric scalable MD scalar quantizer. These descriptions are then layered Wyner-Ziv (WZ) coded using low-density parity-check accumulate (LDPCA) -based syndrome binning. The decoder consists of two side decoders which attempt to iteratively decode their respective description at various LDPCA puncturing rates in the presence of a correlated side information. A central decoder exploits the inter-description correlation to further enhance the WZ ratedistortion performance when both descriptions are partially or fully received. In contrast to earlier work, our proposed decoding scheme also exploits the correlation that exists between bit-planes. Experimental simulations reveal that, for a Gaussian source, the proposed system yields a performance improvement of roughly 0.66 dB when compared to not exploiting inter-description correlations.",
keywords = "multiple description coding, distributed source coding, cross-decoding, layered WZ-coding",
author = "Beerend Ceulemans and Shahid Satti and Nikolaos Deligiannis and Frederik Verbist and Adrian Munteanu",
year = "2014",
language = "English",
isbn = "978-1-4799-4603-7",
series = "Proceedings of the European Signal Processing Conference",
publisher = "IEEE",
pages = "835--839",
booktitle = "2014 Proceedings of the 22nd European Signal Processing Conference",
note = "22nd European Signal Processing Conference, EUSIPCO 2014 ; Conference date: 01-09-2014 Through 05-09-2014",
}